{"id":"W2887495264","doi":"10.24200/sci.2018.50953.1934","title":"Prediction of meteorological and hydrological phenomena by different climatic scenarios in the Karkheh watershed (south west of Iran)","year":2018,"lang":"en","type":"article","venue":"Scientia Iranica","topic":"Climate variability and models","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Watershed; Environmental science; Climatology; Hydrology (agriculture); Meteorology; Geology; Geography; Geotechnical engineering; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001420511,0.0001179515,0.0002289985,0.00003261956,0.0001035247,0.00001895868,0.0003529197,0.00008540455,0.001176059],"category_scores_gemma":[0.00005439659,0.00006563524,0.00005381219,0.0002357173,0.001324462,0.0001005172,0.0002420938,0.0001145551,0.00002445799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003115905,"about_ca_system_score_gemma":0.000003204167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007761693,"about_ca_topic_score_gemma":0.0001029695,"domain_scores_codex":[0.9984207,0.0001916857,0.0003893457,0.0003671944,0.0003605783,0.0002704772],"domain_scores_gemma":[0.9994132,0.00009228378,0.0001082354,0.0003192531,0.000007748728,0.00005930743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002608862,0.001644495,0.6336838,0.00007699683,0.00002821164,0.000002007529,0.01640295,0.0003769411,0.3453155,0.0007155668,0.0004961546,0.0009964061],"study_design_scores_gemma":[0.001999587,0.001935787,0.9439891,0.00003745447,0.0001087225,0.000008193229,0.0009009122,0.04142013,0.004295541,0.004562091,0.000487109,0.0002553584],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972042,0.00002190931,0.0002116043,0.0004165205,0.00006498933,0.0003241466,0.00003514747,0.00001244218,0.00170902],"genre_scores_gemma":[0.9996064,0.00001426563,0.0001997955,0.0001262548,0.00001341412,0.00001149665,0.00001020128,0.000003749765,0.00001444808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.34102,"threshold_uncertainty_score":0.999737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03347363795900937,"score_gpt":0.2266160939049455,"score_spread":0.1931424559459361,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}